Artifacts in image data sets recorded with X-rays that are reconstructed from projection images may originate in objects of higher density lying inside or outside the reconstruction volume. Objects of this kind generally have a higher density and/or a higher attenuation coefficient than naturally occurring materials in the body of a person, which is usually recorded as the object under examination. Such artifacts are particularly frequently artifacts resulting from metal objects and so may also be designated metal artifacts.
To date, a plurality of methods have been suggested for correcting or avoiding metal artifacts or other artifacts resulting from strongly attenuating objects when the object is located within the actual reconstruction volume. In this case, it is usual to segment the object in the image data set or a previously reconstructed reconstruction data set of the reconstruction volume. In this way, the voxels included in the object are identified in the three-dimensional reconstruction volume and also located in the two-dimensional projection images by forward projection. An interpolation method may be used to compensate the object traces, in particular metal traces, in the projection images. The final image data set is then generated during a second reconstruction using the corrected projection images. In this way, the second reconstruction contains fewer metal artifacts than the first reconstruction. Here, it is generally the case that the quality of the correction method is mainly determined by the quality of the segmentation of the object in the reconstruction data set of the first reconstruction.
However, this concept cannot be used if the object giving rise to the artifacts does not appear in the reconstruction volume (nominal measuring field). Here, the reconstruction volume is the area covered by all the projection images (e.g., usually by a projection image interval of at least 180°, in particular 180° plus the fan angle). The reconstruction volume is the area that is ultimately also to be reconstructed in the image data set while the projection data is not complete for all objects and structures outside the reconstruction volume so that it is also not possible to produce a complete and correct depiction of the objects. However, it is also the case that when objects, in particular metal objects, are present outside the reconstruction volume, for example fixation screws, markers and the like, the objects are also able to generate artifacts in a reconstructed image data set for the reconstruction volume since these objects may be seen in at least a part of the projection images that are a part of the raw data. Even if only a few projection images represent the object, it is still possible for the object to give rise to artifacts.
To date, there has been no practicable solution for effective artifact correction where an object is located outside the reconstruction volume. The known methods work on the basis of a segmentation of the objects in the three-dimensional reconstruction volume. Methods are also known which use a raw-data-based estimation of the positions of objects in sinograms. These methods also do not produce satisfactory results when the objects are only visible in a few projection images.